code: def make_inputs(shapes, num_numbers=0):
      inputs = [torch.randn(shape) for shape in shapes]
      num_symbols = max(map(len, shapes)) if shapes else 0
      for _ in range(num_numbers):
          inputs.append(random.random())
      dim_to_symbol = {}
      symbol_to_dim = {}
      for dim, symbol in zip(
          range(-num_symbols, 0), "abcdefghijklmnopqrstuvwxyz"
      ):
          dim_to_symbol[dim] = symbol
          symbol_to_dim[symbol] = dim
      return inputs, dim_to_symbol, symbol_to_dim
  
file_path: pyro/tests/ops/test_packed.py
imports: import itertools
  import random
  import pytest
  import torch
  from torch.distributions.utils import broadcast_all
  from pyro.ops import packed
  from tests.common import assert_equal
label_desc: Use image node_id 2 for calling a global function with example usage: make_inputs(shapes, num_numbers) and returns: inputs,  dim_to_symbol,  symbol_to_dim